INE Highlights Enterprise Shift Toward Hands-On Training Amid Widening Skills Gaps
As AI accelerates job transformation, INE supports organizations reallocating Q4 budgets to experiential, performance-driven upskilling.
Security | Threat Detection | Cyberattacks | DevSecOps | Compliance
The Latest Cybersecurity News & Insights From Around The World
It's 2 AM. Do You Know Which AIs Your MCP Server Is Talking To?
When Anthropic dropped the Model Context Protocol (MCP) in late 2024, it felt like the missing puzzle piece for AI tooling: a standard way for Large Language Models (LLMs) to talk to data sources, APIs, and pretty much anything else you can think of. Think of it as a USB-C port for AI, as the protocol’s creators like to say. But like most shiny new standards, the devil’s in the details.
2026 API and AI Security Predictions: What Experts Expect in the Year Ahead
This is a predictions blog. We know, we know; everyone does them, and they can get a bit same-y. Chances are, you’re already bored with reading them. So, we’ve decided to do things a little bit differently this year. Instead of bombarding you with just our own predictions, we’ve decided to cast the net far and wide. We’ve spoken to cybersecurity experts from around the world to answer what’s, for us, the most pressing question of all.
All things AI and malware with Randy Pargman
Join us for this week's Defender Fridays as we explore the reality of AI-powered malware threats with Randy Pargman, Senior Director of Threat Detection at Proofpoint. At Defender Fridays, we delve into the dynamic world of information security, exploring its defensive side with seasoned professionals from across the industry. Our aim is simple yet ambitious: to foster a collaborative space where ideas flow freely, experiences are shared, and knowledge expands.
How to choose AI security tools that actually reduce false positives
Let’s be honest: if your SOC is drowning in noise, you’re not “doing security.” You’re babysitting tools that cry wolf. And the wolves? They’re doing just fine. Every vendor claims their AI magically cuts false positives. Most don’t. Why?
AI-Native Browsers Demand AI-Native Security: Why Legacy DLP Can't Protect You
In our recent analysis of AI browser exfiltration risks, we exposed how OpenAI's Atlas and Perplexity's Comet create permanent backdoors to sensitive data through persistent memory, autonomous agents, and cross-platform sync. The challenges with AI native browsers strongly resonated with CISO’s and security leaders we speak with on a daily basis. But the threat extends far beyond Atlas and Comet.
PII Detection in Unstructured Text: Why Regex Fails (And What Works)
Let’s look at something many teams quietly struggle with. Detecting PII inside unstructured text. It feels like it should be simple. After all, we’ve used regular expressions for years to find emails, phone numbers, and ID formats. Yet when we deploy regex in real environments. ticket systems, chat logs, CRM notes, uploaded documents, support transcripts. something becomes clear very quickly. Regex isn’t enough.
Adversarial AI: The New Symmetric Threat Landscape
Adversarial AI is geometrically making cyber a symmetric threat, fundamentally altering the cybersecurity equation. However, there are leaders who have successfully navigated these emerging challenges and understand the implications. Join Dr. Aleksandr Yampolskiy (CEO & Co-Founder, SecurityScorecard) and Dr. Srinivas Mukkamala (CEO, Securin Inc.) as they dive into: SecurityScorecard monitors and scores over 12 million companies worldwide.
The problem? The people you're blocking are often top performers.
Banning AI seems logical. Our new report shows why it's failing. The problem? The people you're blocking are often top performers. They're confident, innovative, and willing to work around the rules to get value. This video explains why this paradox changes everything. You can't just block curiosity. You have to harness it. Download the complete (ungated) report.
Data Leakage: AI's Plumbing Problem
Sensitive information disclosure ranks on the OWASP Top 10 for LLM Applications, and for good reason. When AI-powered applications inadvertently expose private data like personally identifiable information (PII), financial records, health information, API keys, or proprietary business intelligence, the consequences cascade quickly: regulatory violations, competitive disadvantage, and shattered user trust.